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Literature Search and Analysis in Faraday

Faraday provides powerful AI-driven literature search and analysis capabilities to help you stay current with the latest scientific developments and extract actionable insights from vast amounts of research. From discovering novel targets to understanding competitive landscapes, Faraday can automatically extract structured insights from unstructured scientific text across major preprint servers and publications.

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AI-Powered Literature Analysis

Automatically extract structured insights from unstructured scientific text across multiple sources including bioRxiv, medRxiv, chemRxiv, and traditional publications. Faraday’s AI scientist can read, analyze, and synthesize information from thousands of papers to answer complex research questions.

Key example capabilities include:

  • Target discovery – Identify novel therapeutic targets and mechanisms
  • Biomarker identification – Discover diagnostic and prognostic markers
  • Drug repurposing – Find new applications for existing compounds

Sample prompts:

  • Are there any novel targets for Alzheimer’s disease reported since 2020?
  • What are the latest developments in CAR-T cell therapy for solid tumors?
  • Find structure-activity relationships for KRAS G12C inhibitors
  • What safety concerns have been reported for GLP-1 agonists?
  • Identify biomarkers for early detection of pancreatic cancer
  • What are the emerging trends in cancer immunotherapy?
  • Find repurposing opportunities for metformin beyond diabetes
  • Analyze the competitive landscape for CDK4/6 inhibitors

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Example:

Let’s try the following query:

Q: Are there any novel targets for Alzheimer’s disease reported since 2020?

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Try it out

Try it for yourself on the platform